Developing Digital Therapeutics for Chronic Pain in Primary Care: A Qualitative Human-Centered Design Study of Providers' Motivations and Challenges.

BACKGROUND: Digital therapeutics are growing as a solution to manage pain for patients; yet, they are underused in primary care where over half of the patients with chronic pain seek care. Little is known about how to successfully engage primary care providers in recommending digital therapeutics to their patients. Exploring provider motivations in chronic pain management would potentially help to improve their engagement and inform the development of digital therapeutics. OBJECTIVE: This study examined primary care providers' motivations for chronic pain management, including their strategies and challenges, to inform the future development of chronic pain-related digital therapeutics tailored to primary care settings. METHODS: We conducted qualitative semistructured interviews with health care providers recruited from 3 primary care clinics in Washington and 1 clinic in Colorado between July and October 2021. The sample (N=11) included 7 primary care physicians, 2 behavioral health providers, 1 physician assistant, and 1 nurse. Most providers worked in clinics affiliated with urban academic health systems. Guided by the human-centered design approach and Christensen's Job-to-be-Done framework, we asked providers their goals and priorities in chronic pain management, their experiences with challenges and strategies used to care for patients, and their perceptions of applying digital therapeutics in clinical practice. Transcripts were analyzed using a thematic analysis approach. RESULTS: We found that primary care providers were motivated but challenged to strengthen the patient-provider alliance, provide team-based care, track and monitor patients' progress, and address social determinants of health in chronic pain management. Specifically, providers desired additional resources to improve patient-centered communication, pain education and counseling, and goal setting with patients. Providers also requested greater accessibility to multidisciplinary care team consultations and nonpharmacological pain treatments. When managing chronic pain at the population level, providers need infrastructure and systems to systematically track and monitor patients' pain and provide wraparound health and social services for underserved patients. Recommendations on digital therapeutic features that might address provider challenges in achieving these motivations were discussed. CONCLUSIONS: Given the findings, to engage primary care providers, digital therapeutics for chronic pain management need to strengthen the patient-provider alliance, increase access to nonpharmacological treatment options, support population health tracking and management, and provide equitable reach. Leveraging digital therapeutics in a feasible, appropriate, and acceptable way to aid primary care providers in chronic pain management may require multimodal features that address provider motivations at an individual care and clinic or system level.

Implementing Brief Tobacco Cessation Interventions in Community Pharmacies: An Application of Rogers' Diffusion of Innovations Theory.

Pharmacists, as highly accessible members of the healthcare team, have considerable potential to address tobacco use among patients. However, while published data suggest that pharmacists are effective in helping patients quit, barriers exist to routine implementation of cessation services in community pharmacy settings. Within the context of a randomized trial (n = 64 pharmacies), surveys were administered over a period of 6 months to assess pharmacists' perceptions of factors associated with the implementation of "Ask-Advise-Refer", a brief intervention approach that facilitates patient referrals to the tobacco quitline. Study measures, grounded in Rogers' Diffusion of Innovations Theory, assessed pharmacists' perceptions of implementation facilitators and barriers, perceptions of intervention materials provided, and perceived efforts and personal success in implementing Ask-Advise-Refer at 6-months follow-up. Findings indicate that while the brief intervention approach was not difficult to understand or implement, integration into normal workflows presents greater challenges and is associated with overall confidence and implementation success. Lack of time was the most significant barrier to routine implementation. Most (90.6%) believed that community pharmacies should be active in promoting tobacco quitlines. Study results can inform future development of systems-based approaches that lead to broad-scale adoption of brief interventions, including but not limited to tobacco cessation, in pharmacy settings.

Analysis of Demographic Characteristics of Users of a Free Tobacco Cessation Smartphone App: Observational Study.

BACKGROUND: Tobacco use continues to be the leading preventable cause of death, disease, and disability in the United States. Since 2000, Washington state has offered free tobacco "quitline" services to help its residents stop using tobacco. In 2015, the state began offering free access to a tobacco cessation smartphone app to absorb excess quitline demand. Since most publicly funded tobacco cessation programs are designed to provide access to populations disproportionately impacted by tobacco use, it is important to consider who these public health interventions reach. OBJECTIVE: The aim of this study is to understand who used a free cessation app and the extent to which users represented populations disproportionately impacted by tobacco use. METHODS: This is an observational study of 1280 adult Washington state residents who registered for and activated the cessation app. Demographic data were collected as part of the sign-up process, examined using standard descriptive measures, and assessed against state-level surveillance data for representativeness. RESULTS: Participants were primarily non-Hispanic White (978/1218, 80.3%), identified as female (780/1236, 63.1%), were between ages 25-54 years (903/1186, 76.1%), had at least some college education (836/1222, 68.4%), and reported a household income under US $50,000 (742/1055, 70.3%). Fewer respondents were from rural counties (359/1220, 29.4%); identified as lesbian, gay, bisexual, pansexual, queer, questioning, or asexual (LGBQA; 153/1222, 12.5%); were uninsured (147/1206, 12.2%); or were currently pregnant, planning pregnancy, or breastfeeding (42/624, 6.7%). However, relative to available state data for tobacco users, there was high representation of women, 35- to 54-year-olds, college graduates, and LGBQA individuals, as well as individuals with low household income, poor mental health, Medicaid insurance, and those residing in rural counties. CONCLUSIONS: A diverse population of tobacco users will use a free cessation app, including some demographic groups disproportionately impacted by tobacco use. With high reach and high efficacy, it is possible to address health disparities associated with tobacco use and dependence treatment among certain underserved and at-risk groups.

Implementation of Ask-Advise-Connect in a safety net healthcare system: quitline treatment engagement and smoking cessation outcomes.

Ask-Advise-Connect (AAC) was designed to link smokers in primary care settings with evidence-based tobacco treatment delivered via state quitlines. AAC involves training medical staff to Ask about smoking status, Advise smokers to quit, and offer to immediately Connect smokers with quitlines through an automated link within the electronic health record. We evaluated the efficacy of AAC in facilitating treatment engagement and smoking abstinence in a 34 month implementation trial conducted in a large, safety-net health care system. AAC was implemented from April 2013 through February 2016 in 13 community clinics that provided care to low-income, predominantly racial/ethnic minority smokers. Licensed vocational nurses were trained to implement AAC as part of standard care. Outcomes included (a) treatment engagement (i.e., proportion of identified smokers that enrolled in treatment) and (b) self-reported and biochemically confirmed abstinence at 6 months. Smoking status was recorded for 218,915 unique patients, and 40,888 reported current smoking. The proportion of all identified smokers who enrolled in treatment was 11.8%. Self-reported abstinence at 6 months was 16.6%, and biochemically confirmed abstinence was 4.5%. AAC was successfully implemented as part of standard care. Treatment engagement was high compared with rates of engagement for more traditional referral-based approaches reported in the literature. Although self-reported abstinence was in line with other quitline-delivered treatment studies, biochemically confirmed abstinence, which is not routinely captured in quitline studies, was dramatically lower. This discrepancy challenges the adequacy of self-report for large, population-based studies. A more detailed and comprehensive investigation is warranted.

Large-scale influenza vaccination promotion on a mobile app platform: A randomized controlled trial.

While health-care providers have used incentives in an attempt to motivate patients to obtain vaccinations, their effect on vaccination rates has not been systematically evaluated on a large scale. In this study, we examined whether mobile applications may improve population vaccination rates through enhanced communication and incentives education. Our study is the first randomized controlled trial assessing the effect of large-scale messaging combined with individualized incentives on influenza-vaccination rates. In this trial, we delivered messages regarding influenza vaccinations to 50,286 adults, aged 18 through 65, then compared the subsequent vaccination rate, the effectiveness of the message content and the timing. Multiple rounds of messaging occurred over a seven-week period during the 2016 flu season, after which vaccination rates were observed for one week. Participants were randomly assigned to one of three messaging approaches: conspicuous (highlighting the amount of rewards to be received for obtaining a flu shot); generic (promoting vaccinations with no mention of rewards); or no-message. Evidence of vaccination obtainment was indicated by medical and pharmacy claims, augmented by patients self-reporting through the mobile wellness app during the study period. Of the people assigned to receive messaging, 23.2% obtained influenza vaccination, compared to 22.0% of people who obtained vaccination in the no-messaging control arm. This difference was statistically significant (p < 0.01). The research revealed that messaging effectiveness decreased after each successive batch sent, suggesting that most participants responsive to messaging would become activated immediately after receiving one alert. Interestingly, in this large-scale study, there were no significant differences between conspicuous incentives and generic messaging, suggesting an important area for future research. Trial Registration: clinicaltrials.gov identifier: NCT02908893.

Correction: The Association Between Medication Adherence for Chronic Conditions and Digital Health Activity Tracking: Retrospective Analysis.

[This corrects the article DOI: 10.2196/11486.].

The Association Between Medication Adherence for Chronic Conditions and Digital Health Activity Tracking: Retrospective Analysis.

BACKGROUND: Chronic diseases have a widespread impact on health outcomes and costs in the United States. Heart disease and diabetes are among the biggest cost burdens on the health care system. Adherence to medication is associated with better health outcomes and lower total health care costs for individuals with these conditions, but the relationship between medication adherence and health activity behavior has not been explored extensively. OBJECTIVE: The aim of this study was to examine the relationship between medication adherence and health behaviors among a large population of insured individuals with hypertension, diabetes, and dyslipidemia. METHODS: We conducted a retrospective analysis of health status, behaviors, and medication adherence from medical and pharmacy claims and health behavior data. Adherence was measured in terms of proportion of days covered (PDC), calculated from pharmacy claims using both a fixed and variable denominator methodology. Individuals were considered adherent if their PDC was at least 0.80. We used step counts, sleep, weight, and food log data that were transmitted through devices that individuals linked. We computed metrics on the frequency of tracking and the extent to which individuals engaged in each tracking activity. Finally, we used logistic regression to model the relationship between adherent status and the activity-tracking metrics, including age and sex as fixed effects. RESULTS: We identified 117,765 cases with diabetes, 317,340 with dyslipidemia, and 673,428 with hypertension between January 1, 2015 and June 1, 2016 in available data sources. Average fixed and variable PDC for all individuals ranged from 0.673 to 0.917 for diabetes, 0.756 to 0.921 for dyslipidemia, and 0.756 to 0.929 for hypertension. A subgroup of 8553 cases also had health behavior data (eg, activity-tracker data). On the basis of these data, individuals who tracked steps, sleep, weight, or diet were significantly more likely to be adherent to medication than those who did not track any activities in both the fixed methodology (odds ratio, OR 1.33, 95% CI 1.29-1.36) and variable methodology (OR 1.37, 95% CI 1.32-1.43), with age and sex as fixed effects. Furthermore, there was a positive association between frequency of activity tracking and medication adherence. In the logistic regression model, increasing the adjusted tracking ratio by 0.5 increased the fixed adherent status OR by a factor of 1.11 (95% CI 1.06-1.16). Finally, we found a positive association between number of steps and adherent status when controlling for age and sex. CONCLUSIONS: Adopters of digital health activity trackers tend to be more adherent to hypertension, diabetes, and dyslipidemia medications, and adherence increases with tracking frequency. This suggests that there may be value in examining new ways to further promote medication adherence through programs that incentivize health tracking and leveraging insights derived from connected devices to improve health outcomes.

Quitline treatment dose predicts cessation outcomes among safety net patients linked with treatment via Ask-Advise-Connect.

The efficacy of tobacco treatment delivered by state quitlines in diverse populations is well-supported, yet little is known about associations between treatment dose and cessation outcomes following the implementation of Ask-Advise-Connect (AAC), an electronic health record-based systematic referral process that generates a high volume of proactive calls from the state quitline to smokers. The current study is a secondary analysis of a 34-month implementation trial evaluating ACC in 13 safety-net clinics in Houston, TX. Treatment was delivered by a quitline and comprised up to five proactive, telephone-delivered multi-component cognitive-behavioral treatment sessions. Associations between treatment dose and abstinence were examined. Abstinence was assessed by phone six months after treatment enrollment, and biochemically confirmed via mailed saliva cotinine. Among smokers who enrolled in treatment and agreed to follow-up (n = 3704), 29.2% completed no treatment sessions, 35.5% completed one session, 16.4% completed two sessions, and 19.0% completed ≥three sessions. Those who completed one (vs. no) sessions were no more likely to report abstinence (OR: 0.98). Those who completed two (vs. no) sessions were nearly twice as likely to report abstinence (OR: 1.83). Those who completed ≥three (vs. no) sessions were nearly four times as likely to report abstinence (OR: 3.70). Biochemically-confirmed cessation outcomes were similar. Most smokers received minimal or no treatment, and treatment dose had a large impact on abstinence. Results highlight the importance of improving engagement in evidence-based treatment protocols following enrollment. Given that motivation to quit fluctuates, systematically offering enrollment to all smokers at all visits is important.

Examining Changes in Healthy Days After Health Coaching.

PURPOSE: To describe changes in health-related quality of life (HRQOL) related to variation in demographic characteristics, program goals, and program participation, among health coaching program participants. DESIGN: A retrospective observational study of a health coaching program. SETTING AND PARTICIPANTS: A total of 2169 adults enrolled in an individually purchased or employer-sponsored health plan from a large health and well-being company, who participated in a health coaching program between January 2016 and April 2017. INTERVENTION: The health coaching program used evidence-based behavior change strategies to encourage skill development, self-monitoring, and goal setting/achievement. Health coaching program modalities included online and telephonic coaching sessions. MEASURES: Demographic characteristics (gender, age, race, income), goal categories (weight management, fitness, nutrition, stress management, other), program modality (online, telephonic, both), engagement level (low, medium, high), and Healthy Days, a validated HRQOL measure developed by the Centers for Disease Control and Prevention. ANALYSIS: t Tests, mixed analysis of variance (ANOVA). RESULTS: There were significant ( P < .05) reductions in average total unhealthy days (UHDs) across all goal categories. Mixed ANOVAs identified a significant main effect for time, for all demographic characteristics ( P values < .05), and a significant effect for program modality ( P < .0001), time ( P < .0001), and interaction effects, between program modality and time, on average UHD ( P = .01). CONCLUSION: Our findings indicate significant reductions in UHD, following 6 months of health coaching, and support the use of HRQOL measures, which are known to be highly correlated with traditional measures of health, to evaluate health coaching programs.

Outcomes of a randomized trial evaluating two approaches for promoting pharmacy-based referrals to the tobacco quitline.

OBJECTIVES: To evaluate the long-term impact of 2 promising intervention approaches to engage pharmacy personnel (pharmacists, technicians) in referring patients who want to quit smoking to the tobacco quitline. DESIGN: Randomized trial. SETTING: Community pharmacies in Connecticut (n = 32) and Washington (n = 32). INTERVENTION: Two intervention approaches were evaluated: academic detailing (AD), which involved on-site training for pharmacy staff about the quitline, versus mailed quitline materials (MM). MAIN OUTCOME MEASURES: Changes in the overall percentage of quitline registrants who reported hearing about the quitline from any pharmacy during the 6-month baseline monitoring period versus the 12-month intervention period, and between-group comparisons of a) the number of quitline registrants who reported hearing about the quitline from one of the study pharmacies during the 12-month intervention period, and b) the number of quitline cards and brochures distributed to patients during the first 6 months of the intervention period. RESULTS: The percentage of quitline callers who reported having heard about the quitline from a pharmacy increased significantly, from 2.2% during the baseline monitoring period to 3.8% during the 12-month intervention (P < 0.0001). In addition, comparisons controlled for seasonal effects also revealed significant increases in referrals. Across all 64 pharmacies, 10,013 quitline cards and 4755 brochures were distributed. The number of quitline cards distributed and the number registrants who reported hearing about the quitline from a pharmacy did not differ by intervention approach (AD vs. MM), although AD pharmacies distributed more quitline brochures (P = 0.022). CONCLUSION: Brief cessation interventions are feasible in community pharmacies, and the 2 approaches evaluated for engaging pharmacy personnel were similarly effective and collectively led to meaningful increases in the number and proportion of all patients who called the quitline. Involvement of community pharmacy personnel in tobacco cessation presents a significant opportunity to promote quitline services by connecting patients with an effective publicly available resource.

Intrapersonal Variation in Goal Setting and Achievement in Health Coaching: Cross-Sectional Retrospective Analysis.

BACKGROUND: Chronic conditions in the United States are among the most costly and preventable of all health problems. Research suggests health coaching is an effective strategy for reducing health risks including decreases in weight, blood pressure, lipids, and blood glucose. Much less is known about how and when coaching works. OBJECTIVE: The aim of this study was to conduct an analysis of intrapersonal variations in participants' progression in health coaching, examining gender and age-related differences. METHODS: This was a cross-sectional, retrospective analysis of 35,333 health coaching participants between 2012 and 2016. Differences in number of goals and activities set and completed, and number of interactions were assessed using negative binomial models. Differences in goal type were assessed using logistic regression for gender and using the Welch test for age to account for unequal variances. RESULTS: Participants choosing online coaching were more likely to be younger and female (P<.001). Gender and age differences were found for the types of goals set by participants. Regarding program activity, women set and completed 12% more action steps than men (P<.001), averaging 21% more interactions than men (P<.001); no gender differences were found in number of goals completed (P=.12), although the percentage of males and females completing goals was significantly different at 60 and 120 days postenrollment (P<.001). Results indicated significant age-related differences in all aspects of program activity: number of interactions, goals set and completed, action steps set and completed (all P values <.01), as well as significant differences in percentage of individuals completing initial goals within 30 days, with older individuals completing more than younger individuals did (all P values <.001). CONCLUSIONS: This study found significant intrapersonal variation in how people participate in and progress through a coaching program. Age-related variations were found in all aspects of coaching activity, from modality preference and initial choice of goal type (eg, weight management, tobacco cessation) to goal completion, whereas gender-related differences were demonstrated for all program activities except number of goals set and completed. These findings indicate that to maximize behavior change, coaches need to personalize the coaching experience to the individual.

Association Between Utilization of Quitline Services and Probability of Tobacco Abstinence in Low-Income Smokers.

INTRODUCTION: Quitlines (QL) are an effective means for smoking cessation, but a paucity of data exist examining the dose-response relationship between use of QL services and quit rates, especially among low-income smokers. The purpose of this study was to study the relationship between tobacco abstinence and use of QL services among low-income smokers. METHODS: Secondary analysis of a randomized trial of every- or some-day smokers aged 18 years or older visiting an urban emergency department. Inclusion criteria included self-pay or Medicaid insurance, as a proxy for low-income and low socioeconomic status. Intervention participants received a motivational interview, 6 weeks of nicotine patches and gum, a referral faxed to the state-sponsored QL, a booster call, and a quitline brochure. Control participants received the brochure. Smoking status was assessed by phone at 1 and 3 months, with confirmation via exhaled carbon monoxide testing at 3 months for those reporting abstinence. QL usage was obtained by utilization data from the QL database. RESULTS: Of 778 subjects, 197 (25.3%) reported any use of QL services at 3 months. Participants were trichotomized: no QL usage, 1 call only, and >1 call (583, 99, and 98 participants, respectively). Quit rates at 3 months in these no, low-, and high-use groups were, respectively, 7.2%, 9.1%, and 15.3% (P=0.03). Participants who used the QL had a median of 28 total minutes of telephone contact. CONCLUSION: Among low-income smokers, greater use of QL services is associated with higher abstinence. Whether this resulted from a direct effect of the QL, or greater motivation among smokers using QL services cannot be determined from these data.

A randomised controlled trial to prevent smoking relapse among recently quit smokers enrolled in employer and health plan sponsored quitlines.

OBJECTIVE: To test adding an interactive voice response (IVR)-supported protocol to standard quitline treatment to prevent relapse among recently quit smokers. DESIGN: Parallel randomised controlled trial with three arms: standard quitline, standard plus technology enhanced quitline with 10 risk assessments (TEQ-10), standard plus 20 TEQ assessments (TEQ-20). SETTING: Quit For Life (QFL) programme. PARTICIPANTS: 1785 QFL enrolees through 19 employers or health plans who were 24+ h quit. INTERVENTIONS: QFL is a 5-call telephone-based cessation programme including medications and web-based support. TEQ interventions included 10 or 20 IVR-delivered relapse risk assessments over 8 weeks with automated transfer to counselling for those at risk. MAIN OUTCOME MEASURES: Self-reported 7-day and 30-day abstinence assessed at 6-month and 12-month post-enrolment (response rates: 61% and 59%, respectively). Missing data were imputed. RESULTS: 1785 were randomised (standard n=592, TEQ-10 n=602, TEQ-20 n=591). Multiple imputation-derived, intent-to-treat 30-day quit rates (95% CI) at 6 months were 59.4% (53.7% to 63.8%) for standard, 62.3% (57.7% to 66.9%) for TEQ-10, 59.4% (53.7% to 65.1%) for TEQ-20 and 30-day quit rates at 12 months were 61.2% (55.6% to 66.8%) for standard, 60.6% (56.0% to 65.2%) for TEQ-10, 54.9% (49.0% to 60.9%) for TEQ-20. There were no significant differences in quit rates. 73.3% of TEQ participants were identified as at-risk by IVR assessments; on average, participants completed 0.41 IVR-transferred counselling calls. Positive risk assessments identified participants less likely (OR=0.56, 95% CI 0.42 to 0.76) to be abstinent at 6 months. CONCLUSIONS: Standard treatment was highly effective, with 61% remaining abstinent at 12 months using multiple imputation intent-to-treat (intent-to-treat missing=smoking quit rate: 38%). TEQ assessments identified quitters at risk for relapse. However, adding IVR-transferred counselling did not yield higher quit rates. Research is needed to determine if alternative designs can improve outcomes. TRIAL REGISTRATION NUMBER: NCT00888992.

Utilization of a Web-based vs integrated phone/Web cessation program among 140,000 tobacco users: an evaluation across 10 free state quitlines.

BACKGROUND: Phone-based tobacco cessation program effectiveness has been established and randomized controlled trials have provided some support for Web-based services. Relatively little is known about who selects different treatment modalities and how they engage with treatments in a real-world setting. OBJECTIVE: This paper describes the characteristics, Web utilization patterns, and return rates of tobacco users who self-selected into a Web-based (Web-Only) versus integrated phone/Web (Phone/Web) cessation program. METHODS: We examined the demographics, baseline tobacco use, Web utilization patterns, and return rates of 141,429 adult tobacco users who self-selected into a Web-Only or integrated Phone/Web cessation program through 1 of 10 state quitlines from August 2012 through July 2013. For each state, registrants were only included from the timeframe in which both programs were offered to all enrollees. Utilization data were limited to site interactions occurring within 6 months after registration. RESULTS: Most participants selected the Phone/Web program (113,019/141,429, 79.91%). After enrollment in Web services, Web-Only were more likely to log in compared to Phone/Web (21,832/28,410, 76.85% vs 23,920/56,892, 42.04%; P<.001), but less likely to return after their initial log-in (8766/21,832, 40.15% vs 13,966/23,920, 58.39%; P<.001). In bivariate and multivariable analyses, those who chose Web-Only were younger, healthier, more highly educated, more likely to be uninsured or commercially insured, more likely to be white non-Hispanic and less likely to be black non-Hispanic, less likely to be highly nicotine-addicted, and more likely to have started their program enrollment online (all P<.001). Among both program populations, participants were more likely to return to Web services if they were women, older, more highly educated, or were sent nicotine replacement therapy (NRT) through their quitline (all P<.001). Phone/Web were also more likely to return if they had completed a coaching call, identified as white non-Hispanic or "other" race, or were commercially insured (all P<.001). Web-Only were less likely to return if they started their enrollment online versus via phone. The interactive Tobacco Tracker, Cost Savings Calculator, and Quitting Plan were the most widely used features overall. Web-Only were more likely than Phone/Web to use most key features (all P<.001), most notably the 5 Quitting Plan behaviors. Among quitlines that offered NRT to both Phone/Web and Web-Only, Web-Only were less likely to have received quitline NRT. CONCLUSIONS: This paper adds to our understanding of who selects different cessation treatment modalities and how they engage with the program in a real-world setting. Web-Only were younger, healthier smokers of higher socioeconomic status who interacted more intensely with services in a single session, but were less likely to re-engage or access NRT benefits. Further research should examine the efficacy of different engagement techniques and services with different subpopulations of tobacco users.

Randomized trial of telephone-delivered acceptance and commitment therapy versus cognitive behavioral therapy for smoking cessation: a pilot study.

OBJECTIVE: We conducted a pilot randomized trial of telephone-delivered acceptance and commitment therapy (ACT) versus cognitive behavioral therapy (CBT) for smoking cessation. METHOD: Participants were 121 uninsured South Carolina State Quitline callers who were adult smokers (at least 10 cigarettes/day) and who wanted to quit within the next 30 days. Participants were randomized to 5 sessions of either ACT or CBT telephone counseling and were offered 2 weeks of nicotine replacement therapy (NRT). RESULTS: ACT participants completed more calls than CBT participants (M = 3.25 in ACT vs. 2.23 in CBT; p = .001). Regarding satisfaction, 100% of ACT participants reported their treatment was useful for quitting smoking (vs. 87% for CBT; p = .03), and 97% of ACT participants would recommend their treatment to a friend (vs. 83% for CBT; p = .06). On the primary outcome of intent-to-treat 30-day point prevalence abstinence at 6 months postrandomization, the quit rates were 31% in ACT versus 22% in CBT (odds ratio [OR] = 1.5, 95% confidence interval [CI] = 0.7-3.4). Among participants depressed at baseline (n = 47), the quit rates were 33% in ACT versus 13% in CBT (OR = 1.2, 95% CI = 1.0-1.6). Consistent with ACT's theory, among participants scoring low on acceptance of cravings at baseline (n = 57), the quit rates were 37% in ACT versus 10% in CBT (OR = 5.3, 95% CI = 1.3-22.0). CONCLUSIONS: ACT is feasible to deliver by phone, is highly acceptable to quitline callers, and shows highly promising quit rates compared with standard CBT quitline counseling. As results were limited by the pilot design (e.g., small sample), a full-scale efficacy trial is now needed.

Outcomes and utilization of a low intensity workplace weight loss program.

Obesity is related to high health care costs and lost productivity in the workplace. Employers are increasingly sponsoring weight loss and wellness programs to ameliorate these costs. We evaluated weight loss outcomes, treatment utilization, and health behavior change in a low intensity phone- and web-based, employer-sponsored weight loss program. The intervention included three proactive counseling phone calls with a registered dietician and a behavioral health coach as well as a comprehensive website. At six months, one third of those who responded to the follow-up survey had lost a clinically significant amount of weight (≥5% of body weight). Clinically significant weight loss was predicted by the use of both the counseling calls and the website. When examining specific features of the web site, the weight tracking tool was the most predictive of weight loss. Health behavior changes such as eating more fruits and vegetables, increasing physical activity, and reducing stress were all predictive of clinically significant weight loss. Although limited by the low follow-up rate, this evaluation suggests that even low intensity weight loss programs can lead to clinical weight loss for a significant number of participants.

Impact of baseline weight on smoking cessation and weight gain in quitlines.

BACKGROUND: The use and effectiveness of tobacco quitlines by weight is still unknown. PURPOSE: This study aims to determine if baseline weight is associated with treatment engagement, cessation, or weight gain following quitline treatment. METHODS: Quitline participants (n = 595) were surveyed at baseline, 3 and 6 months. RESULTS: Baseline weight was not associated with treatment engagement. In unadjusted analyses, overweight smokers reported higher quit rates and were more likely to gain weight after quitting than obese or normal weight smokers. At 3 months, 40 % of overweight vs. 25 % of normal weight or obese smokers quit smoking (p = 0.01); 42 % of overweight, 32 % of normal weight, and 33 % of obese quitters gained weight (p = 0.05). After adjusting for covariates, weight was not significantly related to cessation (approaching significance at 6 months, p = 0.06) or weight gain. CONCLUSIONS: In the first quitline study of this kind, we found no consistent patterns of association between baseline weight and treatment engagement, cessation, or weight gain.

The Ask-Advise-Connect approach for smokers in a safety net healthcare system: a group-randomized trial.

BACKGROUND: Because smoking has a profound impact on socioeconomic disparities in illness and death, it is crucial that vulnerable populations of smokers be targeted with treatment. The U.S. Public Health Service recommends that all patients be asked about their smoking at every visit and that smokers be given brief advice to quit and referred to treatment. PURPOSE: Initiatives to facilitate these practices include the 5A's (ask, advise, assess, assist, arrange) and Ask-Advise-Refer (AAR). Unfortunately, primary care referrals are low, and most smokers referred fail to enroll. This study evaluated the efficacy of the Ask-Advise-Connect (AAC) approach to linking smokers with treatment in a large, safety net public healthcare system. DESIGN: The study design was a pair-matched group-randomized trial with two treatment arms. SETTING/PARTICIPANTS: Ten safety net clinics in Houston TX. INTERVENTION: Clinics were randomized to AAC (n=5; intervention) or AAR (n=5; control). Licensed vocational nurses (LVNs) were trained to assess and record the smoking status of all patients at all visits in the electronic health record. Smokers were given brief advice to quit. In AAC, the names and phone numbers of smokers who agreed to be connected were sent electronically to the Texas quitline daily, and patients were proactively called by the quitline within 48 hours. In AAR, smokers were offered a quitline referral card and encouraged to call on their own. Data were collected between June 2010 and March 2012 and analyzed in 2012. MAIN OUTCOME MEASURES: The primary outcome was impact, defined here as the proportion of identified smokers that enrolled in treatment. RESULTS: The impact (proportion of identified smokers who enrolled in treatment) of AAC (14.7%) was significantly greater than the impact of AAR (0.5%), t(4)=14.61, p=0.0001, OR=32.10 (95% CI=16.60, 62.06). CONCLUSIONS: The AAC approach to aiding smoking cessation has tremendous potential to reduce tobacco-related health disparities.

Use and effectiveness of quitlines for smokers with diabetes: cessation and weight outcomes, Washington State Tobacco Quit Line, 2008.

INTRODUCTION: Having diabetes and smoking increases the risk of morbidity and mortality. However, cessation-related weight gain, a common side effect during quitting, can further complicate diabetes. Evidence-based telephone quitlines can support quitting but have not been studied adequately in populations with chronic diseases such as diabetes. The purpose of this study was to evaluate the use and effectiveness of a tobacco quitline among tobacco users with diabetes. Cessation-related weight concerns and weight gain were also assessed. METHODS: We administered a telephone-based follow-up survey to tobacco users with and without diabetes 7 months after their enrollment in a quitline. We collected and analyzed data on demographics, tobacco use, dieting, weight concern, quitting success (7- and 30-day point prevalence), and weight gain. We computed summary statistics for descriptive data, χ(2) and t tests for bivariate comparisons, and multivariable analyses to determine correlates of cessation. RESULTS: Tobacco users with diabetes used the quitline in a greater proportion than they were represented in the general population. Quit rates for those with and without diabetes did not differ significantly (24.3% vs 22.5%). No significant differences existed between groups for weight gain at follow-up, regardless of quit status. However, participants with diabetes reported more weight gain in previous quit attempts (34.2% vs 22.4% gained >20 lbs, P = .03). Weight concern was a significant correlate of continued smoking, regardless of diabetes status. CONCLUSIONS: Results suggest that quitlines are effective for participants with diabetes, but tailored interventions that address weight concerns during cessation are needed.